Signal processing for optical computing system

ABSTRACT

The present subject matter relates to methods of high-speed analysis of product samples during production of the product. Light is directed to a portion of a product under analysis and reflected from or transmitted through the product toward optical detectors. Signals from the optical detectors are compared to determine characteristics of the product under analysis. Temperature within the monitoring system may be monitored in order to provide compensation for the signals produced by the optical detectors. The products under analysis may be stationary, moved by an inspection point by conveyor or other means, or may be contained within a container, the container including a window portion through which the product illuminating light may pass.

This application claims priority under 35 USC 119(e) of ProvisionalPatent Application Ser. No. 60/856,192 filed Nov. 2, 2006, entitled“IMPROVED SIGNAL PROCESSING FOR OPTICAL COMPUTING SYSTEM,” which ishereby incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present subject matter relates to system design, fabrication andoperation of multivariate optical elements. More particularly, thepresent subject matter relates to methodologies of using multivariateoptical computing systems to illuminate a sample such that informationabout the sample can be analyzed from reflected or transmitted light inreal time or near real time.

BACKGROUND OF THE INVENTION

Light conveys information through data. When light interacts withmatter, for example, it carries away information about the physical andchemical properties of the matter. A property of the light, for example,its intensity, may be measured and interpreted to provide informationabout the matter with which it interacted. That is, the data carried bythe light through its intensity may be measured to derive informationabout the matter. Similarly, in optical communications systems, lightdata is manipulated to convey information over an optical transmissionmedium, for example fiber optic cable. The data is measured when thelight signal is received to derive information.

In general, measurement of light intensity may be difficult to convertto information due to contained interfering data. That is, severalfactors may contribute to the intensity of light, even in a relativelyrestricted wavelength range. It is often impossible to adequatelymeasure the data relating to one of these factors since thecontributions from other factors may be unknown.

It is possible, however, to derive information from light. An estimatemay be obtained, for example, by separating light from several samplesinto wavelength bands and performing a multiple linear regression of theintensity of these bands against the results of conventionalmeasurements of the desired information for each sample. For example, apolymer sample may be illuminated so that light from the polymer carriesinformation regarding the sample's ethylene content. Light from each ofseveral samples may be directed to a series of bandpass filters whichseparate predetermined wavelength bands from the light. Light detectorsfollowing the bandpass filters measure the intensity of each light band.If the ethylene content of each polymer sample is measured usingconventional means, a multiple linear regression of ten measuredbandpass intensities against the measured ethylene content for eachsample may produce an equation such as:y=a ₀ +a ₁ w ₁ +a ₂ w ₂ + . . . +a ₁₀ w ₁₀  (“Equation 1”)where y is ethylene content, a_(n) are constants determined by theregression analysis, and w_(n) is light intensity for each wavelengthband.

Equation 1 may be used to estimate ethylene content of subsequentsamples of the same polymer type. Depending on the circumstances,however, the estimate may be unacceptably inaccurate since factors otherthan ethylene may affect the intensity of the wavelength bands. Theseother factors may not change from one sample to the next in a mannerconsistent with ethylene.

A more accurate estimate may be obtained by compressing the data carriedby the light into principal components. To obtain the principalcomponents, spectroscopic data is collected for a variety of samples ofthe same type of light, for example from illuminated samples of the sametype of polymer. For example, the light samples may be spread into theirwavelength spectra by a spectrograph so that the magnitude of each lightsample at each wavelength may be measured. This data is then pooled andsubjected to a linear-algebraic process known as singular valuedecomposition (SVD). SVD is at the heart of principal componentanalysis, which should be well understood by those of ordinary skill inthis art. Briefly, however, principal component analysis is a dimensionreduction technique, which takes in spectra with n independent variablesand constructs a new set of eigenvectors that are linear combinations ofthe original variables. The eigenvectors may be considered a new set ofplotting axes. The primary axis, termed the first principal component,is the vector, which describes most of the data variability. Subsequentprincipal components describe successively less sample variability,until only noise is described by the higher order principal components.

Typically, the principal components are determined as normalizedvectors. Thus, each component of a light sample may be expressed asx_(n), z_(n), where x_(n) is a scalar multiplier and z_(n) is thenormalized component vector for the n_(th) component. That is, z_(n) isa vector in a multi-dimensional space where each wavelength is adimension. As should be well understood, normalization determines valuesfor a component at each wavelength so that the component maintains itshape and so that the length of the principal component vector is equalto one. Thus, each normalized component vector has a shape and amagnitude so that the components may be used as the basic buildingblocks of all light samples having those principal components.Accordingly, each light sample may be described in the following formatby the combination of the normalized principal components multiplied bythe appropriate scalar multipliers:x ₁ z ₁ +x ₂ z ₂ + . . . +x _(n) z _(n).

The scalar multipliers x_(n) may be considered the “magnitudes” of theprincipal components in a given light sample when the principalcomponents are understood to have a standardized magnitude as providedby normalization.

Because the principal components are orthogonal, they may be used in arelatively straightforward mathematical procedure to decompose a lightsample into the component magnitudes, which accurately describe the datain the original sample. Since the original light sample may also beconsidered a vector in the multi-dimensional wavelength space, the dotproduct of the original signal vector with a principal component vectoris the magnitude of the original signal in the direction of thenormalized component vector. That is, it is the magnitude of thenormalized principal component present in the original signal. This isanalogous to breaking a vector in a three dimensional Cartesian spaceinto its X, Y and Z components. The dot product of the three-dimensionalvector with each axis vector, assuming each axis vector has a magnitudeof 1, gives the magnitude of the three dimensional vector in each of thethree directions. The dot product of the original signal and some othervector that is not perpendicular to the other three dimensions providesredundant data, since this magnitude is already contributed by two ormore of the orthogonal axes.

Because the principal components are orthogonal, or perpendicular, toeach other, the dot, or direct, product of any principal component withany other principal component is zero. Physically, this means that thecomponents do not interfere with each other. If data is altered tochange the magnitude of one component in the original light signal, theother components remain unchanged. In the analogous Cartesian example,reduction of the X component of the three dimensional vector does notaffect the magnitudes of the Y and Z components.

Principal component analysis provides the fewest orthogonal componentsthat can accurately describe the data carried by the light samples.Thus, in a mathematical sense, the principal components are componentsof the original light that do not interfere with each other and thatrepresent the most compact description of the entire data carried by thelight. Physically, each principal component is a light signal that formsa part of the original light signal. Each has a shape over somewavelength range within the original wavelength range. Summing theprincipal components produces the original signal, provided eachcomponent has the proper magnitude.

The principal components comprise a compression of the data carried bythe total light signal. In a physical sense, the shape and wavelengthrange of the principal components describe what data is in the totallight signal while the magnitude of each component describes how much ofthat data is there. If several light samples contain the same types ofdata, but in differing amounts, then a single set of principalcomponents may be used to exactly describe (except for noise) each lightsample by applying appropriate magnitudes to the components.

The principal components may be used to accurately estimate informationcarried by the light. For example, suppose samples of a certain brand ofgasoline, when illuminated, produce light having the same principalcomponents. Spreading each light sample with a spectrograph may producewavelength spectra having shapes that vary from one gasoline sample toanother. The differences may be due to any of several factors, forexample differences in octane rating or lead content.

The differences in the sample spectra may be described as differences inthe magnitudes of the principal components. For example, the gasolinesamples might have four principal components. The magnitudes x_(n) ofthese components in one sample might be J, K, L, and M, whereas in thenext sample the magnitudes may be 0.94 J, 1.07K, 1.13 L and 0.86M. Asnoted above, once the principal components are determined, thesemagnitudes exactly describe their respective light samples.

Refineries desiring to periodically measure octane rating in theirproduct may derive the octane information from the component magnitudes.Octane rating may be dependent upon data in more than one of thecomponents. Octane rating may also be determined through conventionalchemical analysis. Thus, if the component magnitudes and octane ratingfor each of several gasoline samples are measured, a multiple linearregression analysis may be performed for the component magnitudesagainst octane rating to provide an equation such as:y=a ₀ +a ₁ x ₁ +a ₂ x ₂ +a ₃ x ₃ +a ₄×4  (“Equation 2”)where y is octane rating, a_(n) are constants determined by theregression analysis, and x₁, x₂, x₃ and x₄ are the first, second, thirdand fourth principal component magnitudes, respectively.

Using Equation 2, which may be referred to as a regression vector,refineries may accurately estimate octane rating of subsequent gasolinesamples. Conventional systems perform regression vector calculations bycomputer, based on spectrograph measurements of the light sample bywavelength. The spectrograph system spreads the light sample into itsspectrum and measures the intensity of the light at each wavelength overthe spectrum wavelength range. If the regression vector in the Equation2 form is used, the computer reads the intensity data and decomposes thelight sample into the principal component magnitudes x_(n) bydetermining the dot product of the total signal with each component. Thecomponent magnitudes are then applied to the regression equation todetermine octane rating.

To simplify the procedure, however, the regression vector is typicallyconverted to a form that is a function of wavelength so that only onedot product is performed. Each normalized principal component vectorz_(n) has a value over all or part of the total wavelength range. Ifeach wavelength value of each component vector is multiplied by theregression constant a_(n) corresponding to the component vector, and ifthe resulting weighted principal components are summed by wavelength,the regression vector takes the following form:y=a ₀ +b ₁ u ₁ +b ₂ u ₂ + . . . +b _(n) u _(n)  (“Equation 3”)where y is octane rating, a₀ is the first regression constant fromEquation 2, b_(n) is the sum of the multiple of each regression constanta_(n) from Equation 2 and the value of its respective normalizedregression vector at wavelength n, and u_(n) is the intensity of thelight sample at wavelength n. Thus, the new constants define a vector inwavelength space that directly describes octane rating. The regressionvector in a form as in Equation 3 represents the dot product of a lightsample with this vector.

Normalization of the principal components provides the components withan arbitrary value for use during the regression analysis. Accordingly,it is very unlikely that the dot product result produced by theregression vector will be equal to the actual octane rating. The numberwill, however, be proportional to the octane rating. The proportionalityfactor may be determined by measuring octane rating of one or moresamples by conventional means and comparing the result to the numberproduced by the regression vector. Thereafter, the computer can simplyscale the dot product of the regression vector and spectrum to produce anumber approximately equal to the octane rating.

In a conventional spectroscopy analysis system, a laser directs light toa sample by a bandpass filter, a beam splitter, a lens and a fiber opticcable. Light is reflected back through the cable and the beam splitterto another lens to a spectrograph. The spectrograph separates light fromthe illuminated sample by wavelength so that a detection device such asa charge couple detector can measure the intensity of the light at eachwavelength. The charge couple detector is controlled by controller andcooled by a cooler. The detection device measures the light intensity oflight from the spectrograph at each wavelength and outputs this datadigitally to a computer, which stores the light intensity over thewavelength range. The computer also stores a previously derivedregression vector for the desired sample property, for example octane,and sums the multiple of the light intensity and the regression vectorintensity at each wavelength over the sampled wavelength range, therebyobtaining the dot product of the light from the substance and theregression vector. Since this number is proportional to octane rating,the octane rating of the sample is identified.

Since the spectrograph separates the sample light into its wavelengths,a detector is needed that can detect and distinguish the relativelysmall amounts of light at each wavelength. Charge couple devices providehigh sensitivity throughout the visible spectral region and into thenear infrared with extremely low noise. These devices also provide highquantum efficiency, long lifetime, imaging capability and solid-statecharacteristics. Unfortunately, however, charge couple devices and theirrequired operational instrumentation are very expensive. Furthermore,the devices are sensitive to environmental conditions. In a refinery,for example, they must be protected from explosion, vibration andtemperature fluctuations and are often placed in protective housingsapproximately the size of a refrigerator. The power requirements,cooling requirements, cost, complexity and maintenance requirements ofthese systems have made them impractical in many applications.

Multivariate optical computing (MOC) is a powerful predictivespectroscopic technique that incorporates a multi-wavelength spectralweighting directly into analytical instrumentation. This is in contrastto traditional data collection routines where digitized spectral data ispost processed with a computer to correlate spectral signal with analyteconcentration. Previous work has focused on performing such spectralweightings by employing interference filters called Multivariate OpticalElements (MOEs). Other researchers have realized comparable results bycontrolling the staring or integration time for each wavelength duringthe data collection process. All-optical computing methods have beenshown to produce similar multivariate calibration models, but themeasurement precision via an optical computation is superior to atraditional digital regression.

MOC has been demonstrated to simplify the instrumentation and dataanalysis requirements of a traditional multivariate calibration.Specifically, the MOE utilizes a thin film interference filter to sensethe magnitude of a spectral pattern. A no-moving parts spectrometerhighly selective to a particular analyte may be constructed by designingsimple calculations based on the filter transmission and reflectionspectra. Other research groups have also performed optical computationsthrough the use of weighted integration intervals and acousto-opticaltunable filters digital mirror arrays and holographic gratings.

The measurement precision of digital regression has been compared tovarious optical computing techniques including MOEs, positive/negativeinterference filters and weighted-integration scanning opticalcomputing. In a high signal condition where the noise of the instrumentis limited by photon counting, optical computing offers a highermeasurement precision when compared to its digital regressioncounterpart. The enhancement in measurement precision for scanninginstruments is related to the fraction of the total experiment timespent on the most important wavelengths. While the detector integratesor co-adds measurements at these important wavelengths, the signalincreases linearly while the noise increases as a square root of thesignal. Another contribution to this measurement precision enhancementis a combination of the Felgott's and Jacquinot's advantage, which ispossessed by MOE optical computing.

While various implementations of Optical Analysis Systems have beendeveloped to enhance measurement accuracy, no design has emerged thatgenerally encompasses all of the desired characteristics as hereafterpresented in accordance with the subject technology.

SUMMARY OF THE INVENTION

In view of the recognized features encountered in the prior art andaddressed by the present subject matter, a method of high-speedprocessing and monitoring of a plurality of sample portions of productshas been developed. In accordance with an exemplary configuration aplurality of portions of pharmaceutical product may be moved past aninspection point where at least one portion of the pharmaceuticalproduct is illuminated with a spectral-specific light though an opticwindow. The window may be configured to focus the spectral-specificlight onto a portion at the inspection point. Reflected light carryinginformation about the portion through at least one multivariate opticalelement falling on a first detector produces a first signal. A portionof the spectral-specific light is deflected toward a second detector,and at least one selected property of the portion is determined at highspeed based upon the detector outputs as the portion moves past theinspection point. The disclosed method also includes measuring andrecording the temperature of the system to enable compensation orcorrection of the detector outputs based on the system temperature.

The product portions may correspond to pharmaceutical tablets, trays orother containers of powders, or partially- or fully-enclosed samplecontainers that are at least partially transparent to light focused ontothe portion. The product portions may be moved past the inspection pointat a rate between about one portion/second and about fiveportions/second, with the monitoring occurring in real-time at highspeeds.

In another aspect of the invention, a method of high-speed processingand monitoring includes moving a product past an inspection point;illuminating at least a portion of the product with a light; directinglight carrying information about the portion through at least onemultivariate optical element to produce a first signal; detecting thefirst signal at a first detector; detecting a deflected portion of thelight at a second detector; and determining at high speed at least oneselected property of the portion as the portion moves past theinspection point based upon the detector outputs. This aspect of theinvention also includes measuring and recording the temperature of thesystem to enable compensation or correction of the detector outputsbased on the system temperature. The product in this aspect may be apharmaceutical tablet, a pharmaceutical powder, a food product, achemical, a liquid, a gas, an emulsion, a solution, and/or a mixture.

BRIEF DESCRIPTION OF THE DRAWINGS

A full and enabling disclosure of the present invention, including thebest mode thereof to one skilled in the art, is set forth moreparticularly in the remainder of the specification, including referenceto the accompanying figures, in which:

FIG. 1 illustrates an exemplary embodiment of a real time measurementsystem in accordance with the present technology.

Repeat use of reference characters throughout the present specificationand appended drawings is intended to represent same or analogousfeatures or elements of the invention.

DETAILED DESCRIPTION OF THE INVENTION

As discussed in the Summary of the Invention section, the presentsubject matter is particularly concerned with an improved methodologyfor high-speed processing and monitoring of a plurality of sampleproduct portions.

Selected combinations of aspects of the disclosed technology correspondto a plurality of different embodiments of the present invention. Itshould be noted that each of the exemplary embodiments presented anddiscussed herein should not insinuate limitations of the present subjectmatter. Features or steps illustrated or described as part of oneembodiment may be used in combination with aspects of another embodimentto yield yet further embodiments. Additionally, certain features may beinterchanged with similar devices or features not expressly mentionedwhich perform the same or similar function.

As used herein, the term “light” is broadly used to mean any form ofradiation or radiative energy including, but not limited to, visiblelight or light in the infrared region. “Light” is also referred toherein as a light signal, a light beam, a light ray and the like to meanany form of radiative energy in the electromagnetic spectrum. Similarly,the term “transmission” can mean transmission of radiative energy onto asurface of a sample; penetration, however slight, into a sample such asa particulate sample or opaque fluid sample; or passage through asample.

Further, as used herein, the sample being evaluated can be a solid or afluid including, but not limited to, a powder, a pharmaceutical powdermixed with lactose and other excipient materials, a chemical, a polymer,a petroleum product, a solution, a dispersion, an emulsion andcombinations of these solids and fluids.

Reference will now be made in detail to the presently preferredembodiments of the subject optical computing system. Referring now tothe drawings, FIG. 1 illustrates an optical analysis system 110generally depicting the concept of the present subject matter. As shownin FIG. 1, optical analysis system 110 broadly includes a housing 112,an illumination or light source 114, a chopper wheel 118, one or morespectral elements 120, a focusing lens 126, a beam splitter 128, a firstdetector 130 including a multivariate optical element 148, and a seconddetector 132. Optical analysis system 110 further includesrepresentatively illustrated electrical connection 160, pressurizationsensor 162 and purge gas assembly 164. These representativelyillustrated components are well understood by those of ordinary skill inthe present art and, therefore, further description is not deemednecessary to understand and practice these aspects of the presentsubject matter.

With more particular reference to FIG. 1, illumination source 114provides light 134, which passes through collecting Fresnel lens 116Aand into and through spectral element(s) 120. In an exemplaryconfiguration, illumination source 114 may be rated for at least about10,000 hours of operation, which alleviates a need for redundantillumination sources though such redundant sources may be provided ifdesired. Further, in the illustrated exemplary configuration, collectingFresnel lens 116A may be sized to be about 1.5 square inches and spacedabout 0.6 inches from illumination source 114. Those of ordinary skillin the art will appreciate that these dimensions can be adjustedaccording to particular system requirements and are thus not meant aslimitations of the present subject matter.

As further shown in FIG. 1, light 134 passes through spectral elements120, which filter out undesired wavelengths to define a desired spectralregion in order to target a particular chemical material of interest. Inan exemplary configuration the spectral region may correspond to,1500-2000 nm. Light 134 is focused by focusing Fresnel lens 116B, which,in an exemplary configuration may also be sized to be about 1.5 squareinches and spaced about 1 inch from the chopper wheel 118. As shown, thechopper wheel 118 reflects a portion of light 134 as a calibration orreference light 135 and passes another portion as transmitted light 144.

Calibration light 135 is collimated by lens 158 before reflecting from afirst mirror 124A through an adjustable aperture 112B in a bulkhead 112Aof the housing 112. Aperture 112B is adjustable to control the amount ofthe calibration light 135 passing through the aperture. Finally,calibration light 135 impinges on beam splitter 128 thereby sending aportion 135A of calibration light 135 to the first MOE detector 130 anda portion 135B of calibration light 135 to the second or baselinedetector 132.

With further reference to FIG. 1, it may be seen that transmitted light144 passes from the chopper wheel 118 into collimating Fresnel lens 136,which in this exemplary configuration may be sized to be about 1.5square inches and spaced about 0.6 inches from the chopper wheel 118.Transmitted light 144 passes through another adjustable aperture 112C inthe bulkhead 112A and impinges upon a second mirror 124B, which directstransmitted light 144 toward a sample in a container C. In an exemplaryconfiguration, container C may correspond to a mixing vat or blender.Those of ordinary skill in the art will appreciate that “container” Ccould correspond to a conveyor belt or other device for holding ortransporting the sample and is thus not limited to an enclosedcontainer.

As further illustrated in FIG. 1, transmitted light 144 is focused byfocusing Fresnel lens 126, which in this exemplary configuration may beround and about 15/16 inches in diameter and is adjustable with an innertube 122. Also in this exemplary configuration, lens 126 may bepositioned about 0.6 inches from an outer surface of the container C. Asshown, transmitted light 144, now focused by Fresnel lens 126, passesthrough a transmissive window 113. In an exemplary configurationtransmissive window 113 may be approximately 1 inch in diameter andinclude an anti-reflective (AR) coating disposed on one or both sides ofthe window 113. The AR coating ensures that the chemical process in thecontainer C does not interfere with the measuring process of opticalanalysis system 110. Thus, transmitted light 144 enters the container Cand reflects from the sample as carrier light 146. The sample can be amoving mixture such as aspirin and an excipient being blended in realtime, or a plurality of tablets passing by on a conveyor belt at highspeed.

Referring further to FIG. 1, it will be seen that carrier light 146 isdirected by the tube 122 in a direction of the first detector 130.Eventually, carrier light 146 impinges on beam splitter 128 so that aportion of carrier light 146 passes in a direction of detector 132 forbaselining with portion 135B of calibration light 135. Another portionof carrier light 146 passes through MOE 148, which as noted above, hasbeen selected for the chemical of interest based on the variouscomponents of the system 110. Finally, that portion of carver light 146,having passed through the MOE 148, is focused by lens 150 and receivedby the detector 152. As described above, the two signals collected bythe detectors 152 and 156 can be manipulated, e.g., mathematically, toextract and ascertain information about the sample carried by thecarrier light 146.

Temperature sensor 165 is positioned within housing 112 as illustratedin FIG. 1 and may be used to measure and record the temperature of thesystem. By measuring the system temperature, a known calibration ofdetector response to system temperature can be applied to the detectoroutputs. Changes in system temperature are thus compensated for in thesystem output.

The functionality of the MOC system 110 and improvements as describedabove allows for the collection of the entire spectral range of testingsimultaneously, that is, dynamic real-time detection and measurement maybe provided. This fact is notably different than either a system basedon either a scanning lamp or detector system or a discrete diode arraydetection system. The ability to monitor over the complete spectralrange of interest opens up a re-definition of the term “real-time”measurement and analysis.

For instance, true real-time process measurements are possible. In thecontext of the present disclosure, “real time” is intended to refer toobtaining data without delays attendant to collecting samples or delaysdue to lengthy computer processing of measurement signals. In accordancewith the present technology, process data can be obtained in aninstantaneous or near-instantaneous manner through using the disclosedmeasurement techniques to directly monitor materials of interest whilesuch materials are undergoing process steps. Long delays due toprocessing of measurement signals are avoided by optically processingthe light as it is reflected from the material(s) of interest.

Although specific examples disclosed herein present monitoring theblending of powdered material and examining solid tablets, the generalconcept can be extended to other phases. Non-limiting examples of suchinclude use of the present system in analyzing solids, solutions,emulsions, gases, and dispersions. In addition, while exemplaryembodiments discussed herein use reflectance measurements, measurementsin a transmission or transflectance mode would also be appropriate.

One of ordinary skill in the art will recognize that differingapplications may require modifications and alterations to certaincomponents in order to take full advantage of the presently-disclosedsystems. For instance, more diffusion of light has been observed insolid powders relative to liquids; accordingly, different lenses may beneeded when a liquid is monitored in order to account for suchvariations and achieve more accurate measurements.

The presently-disclosed technology can be applied to real-timemeasurements for a range of industrial applications. These include, butare not limited to monitoring of the blending of pharmaceutical powders,including excipients, additives, and active pharmaceutical materials;blending of other powders, including food and chemicals; monitoringdispersions and bi-phasic mixtures (such as insulin, emulsions); and oiland gas applications, including analyzing water content in oil, or oilcontent in water.

Inclusion of a transmissive window provides physical separation betweenthe measuring device and the process or material being tested.Therefore, this window allows for in-line measurement and/ornon-invasive measurement of parameters such as chemical functionality,including alcohol content of petroleum fractions or tackifier resins.Environmental applications are also conceivable, such as stack gasanalysis, including measurement of NOx, SOx, CO, CO2, or other gases ina gas stream; wastewater analysis and treatment monitoring; andhazardous substance monitoring applications such as mercury vapordetection.

As previously noted, MOC technology in accordance with the presentsubject matter may be used to monitor a wide variety of materials as thematerials are subjected to different processes. In an exemplaryconfiguration, the mixing of powders can be monitored. As materials areblended, the existing art does not allow for continuous, real-time,in-line measurement. Current limitations are the result of severalfactors including: moving of the powders being measured during thecourse of data acquisition and the need to connect analytical equipmentto the measurement point using fiber optic cables. The optical analysissystem in accordance with the present technology is designed to allowfor instantaneous measurement using a measurement point located on thevessel.

Other exemplary embodiments of the present subject matter provide realtime measurement of flowing materials. In such embodiments, the samplingwindow(s) may be located on a pipe or vessel such that interrogatingillumination may be applied to the material. For instance, a port may beincluded on a pipe to allow for sampling of the material inside thepipe. The window may be positioned directly on the pipe, or on a smalldiversion away from the main flow path, as appropriate under thecircumstances. Such embodiments could also include sampling of vaporsystems within a stack to monitor combustion gases or flowing processstream such as water containing other materials.

Still further embodiments of the present subject matter include the realtime measurement of materials in containers, such as vials or bins wherethe container is either at least partially open to the outsideenvironment or transmissive to the sampling illumination. Suchcontainers could be stationary or in motion. A container could alsoinclude a conveyor or trough carrying material. Typical applicationsinclude monitoring the progress of a chemical reaction or the content ofsamples moving past a measurement location.

The present subject matter may be better understood from the followingtests and examples. In a first example, a breadboard system wasconstructed and used to test a mixture of powders. The first systemcomponents included a 20 W Gilway lamp and employed a 5 mm deuteriumoxide (D₂O) and 5 mm Germanium spectral elements. A fiber optic probewas employed as an optical window while a InAr detector was used formeasurements. For this example, a powdered sample with a knowncomposition was placed in a dish and the fiber optic probe was placed incontact with the powder. The output of the detectors was monitored andrecorded.

In a second example, a system was constructed and used to make staticmeasurements on aspirin/lactose. The second example system employedcomponents identical to those of the first sample except for thedetector where a PbS detector from New England Photoconductor wasemployed instead of the InAr detector. For this example, a powderedsample with a known composition was placed in a dish and the systemlight beam was focused on the powder. The output of the detectors wasmonitored and recorded. Aspirin/lactose samples covering the range of100% aspirin to 100% lactose were tested.

In a third example, a system similar to that employed in the secondexample was employed except that a sapphire window was employed to gainaccess to the test material light borne data. In this example,Aspirin/Lactose testing was performed using a mixer bowl containinglactose and the system measured as aspirin was added to the system andmixed. Specifically, lactose powder was placed in the bowl of a mixerand the measurement system was attached the bowl using a Swagelok® brandfitting. A sapphire window was used to contain the powder in the bowland allow the system to interrogate the powder. With the mixer turning,known amounts of aspirin were added and the system output signal wasmonitored and recorded. Aspirin was added in several allotments to about37% final aspirin concentration.

Although the invention has been described in such a way as to provide anenabling disclosure for one skilled in the art to make and use theinvention, it should be understood that the descriptive examples of theinvention are not intended to limit the present invention to use only asshown in the figures. For instance, the housing can be shaped as asquare, an oval, or in a variety of other shapes. Further, a variety oflight sources can be substituted for those described above. It isintended to claim all such changes and modifications as fall within thescope of the appended claims and their equivalents. Thus, whileexemplary embodiments of the invention have been shown and described,those skilled in the art will recognize that changes and modificationsmay be made to the foregoing examples without departing from the scopeand spirit of the invention.

1. A method for high-speed analysis of product samples during productprocessing, comprising: providing an illumination source; illuminatingwith a portion of the light from the illuminating source at least aportion of a product with light at an inspection point; providing firstand second light sensitive detectors, the detectors producing outputsignals based on received light; directing a portion of the light fromthe illuminated product portion toward the first and second lightsensitive detectors, the light from the illuminated product portioncarrying information about the product portion; directing at least aportion of the light from the illumination source toward the first andsecond light sensitive detectors as a reference light; providing atemperature sensor in proximity to the first and second light sensitivedetectors, the temperature sensor producing an output signal based ontemperature; compensating the output signals produced by the first andsecond detectors based on the temperature output signal; and analyzingthe compensated output signals produced by the first and second lightsensitive detectors to determine temperature compensated illuminatedproduct portion information.
 2. The method of claim 1, wherein theproduct is at least one of a pharmaceutical tablet, a pharmaceuticalpowder, a food material, a chemical, a liquid, a gas, an emulsion, asolution, or a mixture thereof.
 3. The method of claim 1, wherein theproduct is a powder mixture in a closed container, the container beingat least partially transparent to the illuminating light.
 4. The methodof claim 1, further comprising: moving the product past the inspectionpoint.
 5. The method of claim 1, wherein directing light from theproduct portion comprises directing light reflected from the productportion.
 6. The method of claim 1, wherein directing light from theproduct portion comprises directing light transmitted through theproduct portion.
 7. The method of claim 1, wherein illuminatingcomprises illuminating the product with a spectral-specific light. 8.The method of claim 7, further comprising: illuminating the productthrough an optic window, the optic window being configured to focus thespectral-specific light onto a product portion at the inspection point.9. The method of claim 1, wherein the product comprises a plurality ofdiscrete portions.
 10. The method of claim 9, wherein the plurality ofdiscrete portions are disposed in closed containers, the containers atleast partially transparent to the spectral-specific light.